Compiler 2/8/13: Where the CI Meets Breaking Bad

08

Feb

2013

THE CI'S MOST FAMOUS CAR WASH OWNER

A recurring theme of Breaking Bad is getting out of difficult situations with science. Yet, you still probably wouldn't expect to run into a character from the hit TV show on the campus of Argonne National Laboratory or University of Chicago. But if you happen to spot a man who looks just like protagonist Walter White's former boss at his car wash job, no need for a double take -- you're not losing your mind. Marius Stan, a Computation Institute Senior Fellow and Argonne scientist studying computational chemistry and physics, provides the memorable eyebrows and Romanian curses for the role of Bogdan, a character who has appeared in a handful of episodes of the AMC drug-trade drama.

This week in the Chicago Tribune, reporter Ted Gregory profiled Stan and told the story of how he got involved with the show when he lived in Albuquerque, before moving to Chicago. Stan might humbly list "Breaking Bad, Bogdan" below a computational microscope and a book about modeling and simulation in materials science on his CI web page. But his colleague, CI fellow Andrew Siegel, said most people at Argonne find his moonlighting career "extremely cool."

"Everybody finds it hilarious and great. In science, you're so uncool, at least in this country, and the world of acting is so opposite of that. It's a funny convergence of things."

THE MATH INSIDE ELECTRICAL OUTLETS

Electrical power grids present a complex and challenging mathematical problem, with questions of how to efficiently produce, store and distribute the energy. To study the mathematics behind tomorrow's power lines, Argonne National Laboratory and Computation Institute scientists formed the Multifaceted Mathematics for Complex Energy Systems Project (M2ACS), which recently received a $17.5 million grant from the Department of Energy. The project will bring together experts from several different areas of mathematical study, including optimization, dynamical systems, uncertainty quantification, random processes, data analysis, discrete mathematics and linear algebra to find new techniques needed to drive next-generation "smart" power grids and other technologies.

CI senior fellow Mihai Anitescu, who is leading the project, described their approach:

"To address these challenges, we will develop, analyze, and integrate predictive models of system behavior, new optimization-based sampling approaches, and new analysis methods and scalable algorithms that can exploit the rich mathematical structure," said Mihai Anitescu, Argonne computational mathematician and director of M2ACS. "Our aim is to create the mathematical underpinnings of the future engineering analysis tools that will ensure the efficiency and resiliency of critical energy systems planning and operations."

OTHER NEWS IN COMPUTATIONAL SCIENCE

Many of the world's largest cities grew to their current size with a minimum of urban planning, chaotic growth outpacing attempts to create an orderly, efficient layout. But as Elizabeth Leake writes at Datanami, our current age of open data and powerful computation creates new opportunities for effective urban planning in cities new and old. Leake reports from last year's International Conference on eScience in Chicago, describing the panel led by the CI's Charlie Catlett on "Designing and operating cities using open data" (also covered on ScaleOut) and the Australia Urban Research Infrastructure Network in Melbourne, Australia. The article includes examples of how the two cities use datasets to track obesity, walkability and food deserts in their respective neighborhoods.

Computation is also making its way into journalism, which is increasingly excited by the promise of data-driven investigations and interactive graphics. For those who couldn't attend, the 2013 Computation + Journalism conference, held last week at Georgia Tech, was helpfully recapped by Reporters' Lab.

A new journal on Big Data called, helpfully, Big Data, premiered with its first issue in January with articles on visualization, life sciences data and "thought crime."